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march (version 3.1)

Markov Chains

Description

Computation of various Markovian models for categorical data including homogeneous Markov chains of any order, MTD models, Hidden Markov models, and Double Chain Markov Models.

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Version

Install

install.packages('march')

Monthly Downloads

187

Version

3.1

License

GPL-2

Maintainer

Andre Berchtold

Last Published

August 18th, 2019

Functions in march (3.1)

march.AIC

Compute Akaike Information Criterion (AIC). The AIC (Akaike Information Criterion) is computed for a given march.Model-class according to the data used during construction.
march-package

Computation of Markovian models for categorical data
march.Dataset-class

Dataset for march package.
march.Model-class

A basic and virtual march model.
march.BIC

Compute Bayesian Information Criterion (BIC).
march.mtd.construct

Construct a Mixture Transition Distribution (MTD) model.
march.name,march.Dcmm-method

This method is called with the object "march.Dcmm" and provides it to the march.name function.
march.Dcmm-class

A Double Chain Markov Model (DCMM).
march.name,march.Mtd-method

This method is called with the object "march.Mtd" and provides it to the march.name function.
march.Mtd-class

A Mixture Transition Distribution (MTD) model.
march.dcmm.construct

Construct a double chain Markov model (DCMM).
march.indep.construct

Construct an independence model (zero-order Markov chain).
march.summary

march.Model Summary.
march.read

Load a march.Model.
march.write

Save a march.Model
march.dcmm.viterbi

Viterbi algorithm for a DCMM model.
march.thompson

Thompson Confidence Intervals for a march.Model.
march.name,march.Mc-method

This method is called with the object "march.MC" and provides it to the march.name function.
sleep_df

Sleep disorders (data frame format)
march.name,march.Indep-method

This method is called with the object "march.Indep" and provides it to the march.name function.
march.dataset.h.extractSequence

Extract a sequence from a dataset.
march.thompson,march.Mc,numeric-method

This method is called with the object "march.Mc" and the aplha "numeric" and provides it to the march.thompson function.
march.name

march.Model name.
pewee

Song of the Wood Pewee (march dataset format)
march.mc.construct

Construct an homogeneous Markov Chain.
pewee_df

Song of the Wood Pewee (data frame format)
march.Indep-class

An independence model.
march.thompson,march.Mtd,numeric-method

This method is called with the object "march.Mtd" and the aplha "numeric" and provides it to the march.thompson function.
march.Mc-class

A Markov chain of order >= 1.
march.dataset.loadFromDataFrame

Construct a dataset from a data.frame or a matrix.
march.dataset.loadFromFile

Load a dataset from a file.
march.thompson,march.Indep,numeric-method

This method is called with the object "march.Indep" and the aplha "numeric" and provides it to the march.thompson function.
march.thompson,march.Dcmm,numeric-method

This method is called with the object "march.Dcmm" and the aplha "numeric" and provides it to the march.thompson function.
sleep

Sleep disorders (march dataset format)
pewee_t

Song of the Wood Pewee (text format)